JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men B. Estimates of the Human Capital Earnings Function 4

As shown earlier, a more direct test of the specific training hypothesis can be obtained if tn, the total duration of the current Job, Is observed.

The results using equation (11) are shown in Table 6, using a small sample of individuals who left the Job they held in 1966 before 1969. The coefficient of the Interaction term (REM x CURRENT) is positive and significant as expected, thus rn pn « .0087. The coefficient of time remaining (REM) is negative and approaching statistical significance, thus pn – .0620. The implied estimate of rn about 14 percent. The results unambiguously suggest that the correlation between Job duration and Investment is a significant determinant of the distribution of earnings. The addition of these two variables Increases the explanatory power of the equation (the F statistic is 2.55, significant at the 10 percent level).
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Young Men

The sample used to study the effects of nobility on earnings at younger ages Is the National Longitudinal Survey of Young Men (aged 14-24 during 1966, the original survey year). Due to the young age range of the Individuals being analyzed and the short duration of the jobs, the analysis Is conducted with two segments of post-school experience: duration of all previous jobs and current job experience. The non-mobile Individuals are defined as those men who have always been In the current job. The data shows that the non-mobile Individuals are younger. This Is because of a selectivity bias inherent In the data: younger men have had less labor force experience, therefore they have had less opportunity to leave the current job , and are thus classified as non-mobile.
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men B. Estimates of the Human Capital Earnings Function 3

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The results presented earlier for those Individuals who were least mobile (Pattern 1) Indicated they Invested heavily on the job as expected since these men currently receive returns on all training ever acquired (net of depreciation), and since they had more Incentive to Invest larger amounts in their only job.
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men B. Estimates of the Human Capital Earnings Function 2

The segmented earnings function (with and without interaction terms) is presented in Table 4 for the pooled sample. As can be seen, the interaction terms are mostly negative, and in fact the addition of the interaction terms to the simpler segmentation in Column 1 significantly Increases the explanatory power of the equation (the F statistic is 2.21, significant at the 10 percent level). Note also that the coefficients of previous experience are significantly weaker than the effect of current experience and that the coefficient of the longest job prior to the current job is by far the largest and most significant of all the previous job coefficients.
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men A. The Sample 2

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In order to pool the samples a simple method Is used throughout. All Individuals are assumed to have a current job. Define FIRST as the first job after completion of schooling, if different from the current job; RESID1 as the residual following the first job; LONGEST as the longest job ever, if different from both the first and current jobs; RESID2 as the residual following the longest job; and CURRENT as the current Job. If a job does not exist for a given Individual, a zero Is coded as his experience for that particular job.

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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men B. Estimates of the Human Capital Earnings Function

Table 3 gives the unsegmented earnings function derived In equation (3) for the pooled sample and across mobility patterns using the natural logarithm of the wage rate as the dependent variable. The explanatory power of the equation Is small. The estimated Investment ratios are larger and more significant for the less mobile, Patterns 1 and 2. For the most mobile men In Pattern 4, the estimate of the Investment ratio Is negative. This result might be caused by two factors: this sample might have an average earnings profile that has already peaked and/or mobile men Invested significantly less than the non-mobile men In on-the-job training, and once the depreciation rate Is taken Into account net Investment becomes zero or negative. Thus even at this level, the basic hypothesis of this paper, namely that job mobility al’fects the rate of growth of earnings adversely, Is confirmed.
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: The Earnings of Older Men A. The Sample

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The National Longitudinal Survey was started in the year 1966 for men aged 45-59 during the original survey. This data provides us with a longitudinal (though retrospective) working life history of older men. Because of the structure of the questionnaire, It Is possible to get, at most, the duration of three Jobs In the individual’s working life: the first full-time Job ever held after completion of schooling, the longest Job isver, and the current Job.
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: Introduction 7

Clearly equation (9) cannot be estimated since the dependent variable Is earnings capacity which Is unobserved. Net earnings can be defined as ~ Cfc, so that In Yg ■ In Eg + In (1 – kg). Y Is closer to the empirically observed earnings since most Investment costs are likely to be forgone earnings. Assuming that kfc Is a small number, In (1 – kfc) * -kg. Equation (9) can then be written as:
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: Introduction 6

A problem Immediately arises since the t* are not observed. For all previoui jobs (1*1,…,n-l), a first-order approximation Is the actual completed job duration. For the current job, tft Is unobserved and no reasonable proxy exists.

lower probability of quitting (and of layoff) than other individuals. Thus:
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Converting (A) into continuous terms, using equations (5)-(8), and integrating yields: Electronic Payday Loans Online
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JOB MOBILITY AND EARNINGS OVER THE LIFE CYCLE: Introduction 5

If we allow for the existence of specific training, dollar investment costs are positively correlated with job duration since higher levels of investment (due partly to the existence of specific training) imply lower turnover rates, ceteris paribus.

The correlation between investment and job duration clearly holds in terms of dollar investment costs. However, the equations derived are in terms of ”time-equivalent” investment costs. So that when using the log-linear equations, a strong assumption must be made: there is a positive correlation between dollar Investment costs and the time spent Investing. The reason for the assumption Is that even though dollar Investment costs and completed job duration are positively correlated, the same need not be true between time-equivalent costs and job duration. The assumption permits us to say that there Is a positive correlation between time Investment and completed experience, since those with longer job duration will have more Investment, but by assumption they spend more time at It. comments
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